All organisms respond to external stimuli in their environment. Changes in the transcriptional regulation of genes are a key component of these responses. Understanding the response of an organism to external stimuli at the biochemical level is necessary to truly understand the resulting physiological changes. In bacteria, biochemically related genes are frequently found in the same operon, resulting in their co-transcription. In some eukaryotes, it is known that some biochemically related genes are under the control of the same transcription factor, which will result in their cotranscription, as described in Greenberg, M. L. et al., “Genetic regulation of phospholipid biosynthesis in Saccharomyces cerevisiae,” Microbiological Reviews. 1: 1-7, 1996, and Batzer, M. A. et al., “Alu repeats and human genomic diversity,” Nat. Rev. Genet. 3: 370-379, 2002.
In plants, little is known about the co-regulation of genes that encode for enzymes that make up biochemical pathways. However, from what is known, it is reasonable to expect many of the enzymes in a biochemical pathway to have genes that are co-regulated in plants. For example, a recent genomic analysis of nitrate-treated Arabidopsis has shown that a set of genes encoding enzymes and cofactors involved in nitrate reduction are induced by nitrate as described in Wang, R. C. et al., “Genomic analysis of a nutrient response in arabidopsis reveals diverse expression patterns and novel metabolic and potential regulatory genes induced by nitrate,” Plant Cell 12:155-171, 2000.
Therefore, the analysis of microarray expression data in relation to metabolic pathways may be a powerful tool in determining the underlying causes of a physiological response in an organism. This realization led to the development of tools to analyze gene expression with respect to pathways. These tools include AraCyc and the PathDB/ISYS/MaxdViewer system. While these tools are useful, they may be currently limited to the analysis of gene expression data only, which is only an approximation of the in vivo level of the protein. Recent advances in measuring metabolite profiles in plants ensure progress in the field of plant metabolomics, as described in Fiehn, O., “Metabolomics—the link between phenotypes and genotypes,” Plant Mol. Biol. 48:155-171, 2002
While the inability to measure the levels of individual proteins in plants in a high-throughput manner currently has limited the growth of the plant proteomics field as described in Kersten, B. et al., “Large-scale plant proteoics,” Plant Mol. Biol. 48:133-141, 2002.
there is remains a need in the bioinformatics arts generally, for a tool capable of analyzing each of proteomic, transcriptosomic and metabolomic types of profile data, either individually or collectively.